Overview of the application of quantitative backscattered electron (QBSE) image analysis to characterize the cement-based materials
•Technical principles, sample preparation, and key factors for QBSE image analysis are introduced.•Different grey-value thresholding methods are discussed.•Application aspects of QBSE image analysis are displayed, including the feature extraction, characterization of temporal evolution, and characte...
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Veröffentlicht in: | Construction & building materials 2023-11, Vol.406, p.133332, Article 133332 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Technical principles, sample preparation, and key factors for QBSE image analysis are introduced.•Different grey-value thresholding methods are discussed.•Application aspects of QBSE image analysis are displayed, including the feature extraction, characterization of temporal evolution, and characterization of spatial evolution.•The merits and limitations of current QBSE image analysis, and the future research directions are presented.
To gain a better understanding of microstructure evolution in cement-based materials, it becomes imperative to characterize their phase proportions and spatial distributions. Cement-based materials are considered typical heterogeneous materials in terms of their microstructure and composition. Due to its remarkable efficiency and versatility, the utilization of quantitative backscattered electron (QBSE) image analysis to characterize cement-based materials has surged recently. This paper aims to provide researchers with insights into selecting a suitable and reliable QBSE image analysis method for their studies. The emphasis is first on the technical principles, sample preparation, and the key factors influencing SEM observations. Then, the development of various QBSE image analysis methods is elucidated. Furthermore, three main application directions, including feature extraction, characterization of temporal evolution, and characterization of spatial evolution, are described to bridge the gap between the methods and practical implementation. Finally, the advantages and limitations associated with QBSE image analysis are discussed. |
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ISSN: | 0950-0618 1879-0526 |
DOI: | 10.1016/j.conbuildmat.2023.133332 |